Learning Orthographic Structure With Sequential Generative Neural Networks

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high‐order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high‐quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non‐connectionist probabilistic models (n‐grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain.     

Parents’ Intelligence Mindsets Relate to Child Internalizing Problems: Moderation Through Child Gender

Parental belief systems can strongly influence children’s affect, behavior, and mental health. However, associations between specific kinds of parental beliefs and children’s mental health have not been thoroughly explored. One relevant belief system is parental intelligence mindset: beliefs about the malleability of intelligence. Children of parents who view intelligence as static (known as a fixed intelligence mindset), rather than malleable through effort (known as a growth intelligence mindset), experience more academic, self-regulatory, and motivational difficulty. However, associations between parental intelligence mindset and child mental health problems are unclear. Accordingly, we tested whether parents’ intelligence mindsets related to internalizing problems in their children (N?=?131, ages 5–8). Overall, parents with stronger fixed intelligence mindsets had children with greater internalizing problems, particularly social anxiety (characterized by fear of negative evaluation). Results further revealed that parents’ fixed intelligence mindsets were associated with overall internalizing problems and depressive symptoms in boys, but not girls. Results are the first to suggest and parse direct links between parents’ intelligence mindsets and youth internalizing problems.     

An Internal Limit of the Structural Analysis of Causation

Structural models of systems of causal connections have become a common tool in the analysis of the concept of causation. In the present paper I offer a general argument to show that one of the most powerful definitions of the concept of actual cause, provided within the structural models framework, is not sufficient to grant a full account of our intuitive judgements about actual causation, so that we are still waiting for a comprehensive definition. This is done not simply by focusing on a set of case studies, but by arguing that our intuitions about two different kinds of causal patterns, i.e., overdetermination and counterdetermination, cannot be addressed using that definition.     

Lateral specialization in unilateral spatial neglect: a cognitive robotics model

In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans.     

The impact of gratitude on depression and anxiety: the mediating role of criticizing,attacking, and reassuring the self

Gratitude significantly predicts less depression and anxiety symptoms in general population. Three types of self-relating processes as possible mediators of this relationship were evaluated. Trait gratitude, depression, anxiety, and three forms of self-relating (criticizing, attacking, and reassuring the self) were assessed in 410 Italian participants. Gratitude predicted less depression and anxiety symptoms, and the three forms of self-relating partially mediated the impact of gratitude on both depression and anxiety. Self-reassuring had a stronger mediation power than self-attacking in the prediction of anxiety symptoms. Gratitude is a protective factor against psychopathology not only due to its association with improved relationships with others, but also because it is connected to a less critical, less punishing, and more compassionate relationship with the self.     

Protective factors for depressive symptoms in emerging adulthood

Emerging adulthood is characterized by pervasive changes in identity and relationships. These challenges can entail problems for subjective well-being, leading to depressive symptoms. The development of an autonomous-related self is considered crucial for emerging adults’ personal growth and psychological well-being. Autonomous-related self is linked to self-esteem and secure attachment style, which are also protective factors for depression. The current research sought to investigate the relation between autonomous-related self and depressive symptoms, as well as the role of secure attachment style and self-esteem, in a sample of 356 Italian emerging adults. Gender differences were taken into account in preliminary analyses. Gender differences emerged for autonomous-related self and self-esteem, while secure attachment and depression levels were similar across gender. Our results suggest that autonomous-related self, mediated by self-esteem and secure attachment style, is a protective factor for emotional states of depression, controlling for social desirability. These findings emphasize the importance of taking autonomy and relatedness into account in emerging adulthood and represent a starting point for future studies.     

Viewing-as explanations and ontic dependence

Philosophical Studies - According to a widespread view in metaphysics and philosophy of science (the “Dependence Thesis”), all explanations involve relations of ontic dependence between...     

Free Will,Values, and Narrative Selfhood

Philosophia - Robert Kane’s libertarian theory of freedom is frequently attacked in the free will literature by the “luck objection”. Alfred Mele’s articulation of the...     

Common Mental Health Challenges in a University Context in Hong Kong: a Study Based on a Review of Medical Records

Applied Research in Quality of Life - While numerous studies have suggested the rising prevalence of common mental disorders amongst university students, studies examining mental health of Chinese...